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techniques Background in biomineralization or structural biology, or desire to work within research that has a marine environmental sustainability perspective Previous work with deep learning frameworks (e.g
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development, and publication in peer-reviewed venues. Strong background in machine learning, with research experience in deep learning, foundation models, or related areas. Solid programming ability in Python
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expertise in deep learning, with experience in at least one of the following: foundation models, transformer architectures, graph neural networks, representation learning, or large-scale training Strong
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mathematical foundation and programming skills in languages such as Python, Java, Julia, MATLAB, R, and/or C++. Expertise in one or more of the following: machine learning, deep learning, HPC, Docker/Singularity
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for screening purposes and cell-based therapies. We will develop methods for modelling missing not at random (MNAR) observations and quantifying uncertainty using Bayesian methods and deep learning architectures
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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studies to identify targets for medical intervention and to generate insight that meaningfully impacts patient care. This position provides direct mentorship from faculty with deep expertise in neuroimaging
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bioinformatics, deep learning and/or biomedical image and clinical data analysis (e.g. Linux, R programming) is essential. The appointees will need to perform data analysis of single cell RNA-sequencing
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the appointment start date; demonstrate strong expertise in computational biology or data-driven modeling, with experience in one or more of the following areas: machine learning or deep learning, structural
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for early-stage cancer using statistics and/or machine learning (including deep learning where appropriate). You will join a vibrant and growing research group of 12 scientists (six postdoctoral researchers